library(dados)
library(tidyverse)
## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
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## ✔ tibble 3.1.8 ✔ dplyr 1.0.10
## ✔ tidyr 1.2.1 ✔ stringr 1.4.1
## ✔ readr 2.1.3 ✔ forcats 0.5.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
library(reactable)
Reactable
dados_sumarizados <- pinguins |>
group_by(especie, ano) |>
summarise(media_comprimento_bico = mean(comprimento_bico, na.rm = TRUE),
media_massa_corporal = mean(massa_corporal, na.rm = TRUE)) |>
ungroup() |>
pivot_wider(names_from = ano,
values_from = c(media_comprimento_bico, media_massa_corporal))
## `summarise()` has grouped output by 'especie'. You can override using the
## `.groups` argument.
dados_sumarizados |>
reactable(sortable = TRUE, searchable = TRUE,
columnGroups = list(
colGroup(name = "Média comprimento de Bico (em milímetros)", c("media_comprimento_bico_2007", "media_comprimento_bico_2008", "media_comprimento_bico_2009")),
colGroup(name = "Média massa corporal (em gramas)", c("media_massa_corporal_2007", "media_massa_corporal_2008", "media_massa_corporal_2009")
)
),
columns = list(
especie = colDef(name = "Espécie"),
media_comprimento_bico_2007 = colDef(name = "2007", format = colFormat(digits = 2, locales = "pt")),
media_comprimento_bico_2008 = colDef(name = "2008", format = colFormat(digits = 2, locales = "pt")),
media_comprimento_bico_2009 = colDef(name = "2009", format = colFormat(digits = 2, locales = "pt")),
media_massa_corporal_2007 = colDef(name = "2007", format = colFormat(digits = 0, separators = TRUE, locales = "pt")),
media_massa_corporal_2008 = colDef(name = "2008", format = colFormat(digits = 0, separators = TRUE, locales = "pt")),
media_massa_corporal_2009 = colDef(name = "2009", format = colFormat(digits = 0, separators = TRUE, locales = "pt"))
)
)
Plotly
grafico_1 <- pinguins |>
ggplot() +
aes(x = comprimento_bico, y = profundidade_bico) +
geom_point(aes(color = especie)) +
theme_bw()
grafico_1
## Warning: Removed 2 rows containing missing values (geom_point).

plotly::ggplotly(grafico_1, tooltip = c("x", "y", "especie"))
library(plotly)
##
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
##
## last_plot
## The following object is masked from 'package:stats':
##
## filter
## The following object is masked from 'package:graphics':
##
## layout
fig <- plot_ly(data = pinguins, x = ~comprimento_bico, y = ~profundidade_bico, color = ~especie)
fig
## No trace type specified:
## Based on info supplied, a 'scatter' trace seems appropriate.
## Read more about this trace type -> https://plotly.com/r/reference/#scatter
## No scatter mode specifed:
## Setting the mode to markers
## Read more about this attribute -> https://plotly.com/r/reference/#scatter-mode
## Warning: Ignoring 2 observations
Highcharter
library(highcharter)
## Registered S3 method overwritten by 'quantmod':
## method from
## as.zoo.data.frame zoo
hchart(pinguins, type = "scatter", hcaes(x = comprimento_bico, y = profundidade_bico, group = especie))